FACTORS CONTRIBUTING TO WELL-BEING: COMPARING FUNCTIONAL SOMATIC SYMPTOM DISORDERS AND WELL-DEFINED AUTOIMMUNE DISORDERS
Bibliographic record
Abstract
"Functional somatic symptom disorders (FSSDs) are defined by persistent and chronic bodily complaints without a pathological explanation. Mindfulness involves the focus on the present moment by noticing surroundings, thoughts, feelings, and events, being nonreactive, being non-judgemental, and self-accepting. Psychological flexibility (PF) involves a focus on the present and the prioritization of thoughts, emotions, and behaviours that align with individual values and goals (Francis et al., 2016). Although PF does not involve a mindfulness practice, the two constructs are related. Research indicates consistent reported positive associations between mindfulness, PF, psychological wellbeing, and medical symptoms. In this study, individuals with FSSDs (fibromyalgia, chronic fatigue syndrome) were compared to those with well-defined autoimmune illnesses (multiple sclerosis, rheumatoid arthritis; AD) to determine how psychosocial factors affect wellness. Participants (N = 609) were recruited from social media and online support groups and completed questionnaires to assess physical health (Chang et al., 2006), psychological wellness (Diener et al., 1985), anxiety (Spitzer et al., 2006), depression (Martin et al., 2006), psychological flexibility, (Francis et al., 2016) and mindfulness (Droutman et al., 2018]. Results indicated that having an FSSD and higher depression was associated with both lower physical and psychological wellness. Interestingly, different aspects of psychological flexibility predicted physical and psychological wellness. These results suggest that different aspects of PF are associated with better physical and psychological health. As PF is modifiable, individuals with chronic conditions could receive training that could ultimately improve their overall health."
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".